Pilot-scale study of phosphorus recovery through struvite crystallization – II: Applying in-reactor supersaturation ratio as a process control parameter
Bibliographic record
Abstract
A pilot-scale MAP (magnesium ammonium phosphate) crystallizer, which was used to remove/recover phosphorus through struvite formation, achieved ortho-P removal rates of over 90%, for a tested high phosphorus concentration (~220 mg/L). The desired degree of P-removal was achieved by either varying the operating pH or the supersaturation ratio at the inlet. The high P-removals (~90%) were achieved even at a pH of 7.3, which is contrary to the information found in the literature, where generally higher pH values (8.2~9) are recommended. This indicates that alkaline pH is not the only factor that can cause the process fluid to be supersaturated. Using solubility criteria, the in-reactor supersaturation ratio was used to define the metastable zone boundaries. The system performance, both in terms of process efficiency and the quality of the harvested product, was at its best when the in-reactor supersaturation ratio was between 1 and 5. The results showed that there was a narrow working zone for optimized crystallization process and a deviation from the optimal metastable zone always resulted in the plugging of the reactor. Key words: conditional solubility product, crystallization, phosphorus removal, struvite.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".